{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualizing activation of hidden layer \n",
    "\n",
    "__Autoencoder__ also helps us to understand how the neural networks work. We can visualize what a node has been experted on. This will give us an intuitive about the way these networks perform.\n",
    "\n",
    "We will implement an autoencoder that takes  images and tries to reconstruct the image. Then we will visualize the activation of the nodes in the hidden layer. We can calculate the activate of node i ($a_{i}$) in the hidden layer with $100$ nodes is:\n",
    "\n",
    "$a_{i} = f(\\sum_{j=1}^{100}W_{ij}^{(1)} + b_{i}^{1})$\n",
    "\n",
    "The input which maximizes the activation of node is:\n",
    "\n",
    "$x_{i} = \\frac{W_{ij}^{1}}{\\sqrt{\\sum_{j=1}^{100}(W_{ij}^{1})}}$\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Imports:\n",
    "We will start with importing the needed libraries for our code."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# imports\n",
    "import tensorflow as tf\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Input data:\n",
    "For this tutorial we use the MNIST dataset. MNIST is a dataset of handwritten digits. If you are into machine learning, you might have heard of this dataset by now. MNIST is kind of benchmark of datasets for deep learning. One other reason that we use the MNIST is that it is easily accesible through Tensorflow. If you want to know more about the MNIST dataset you can check Yann Lecun's website.\n",
    "We can easily import the dataset and see the size of training, test and validation set:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Extracting MNIST_data/train-images-idx3-ubyte.gz\n",
      "Extracting MNIST_data/train-labels-idx1-ubyte.gz\n",
      "Extracting MNIST_data/t10k-images-idx3-ubyte.gz\n",
      "Extracting MNIST_data/t10k-labels-idx1-ubyte.gz\n",
      "Size of:\n",
      "- Training-set:\t\t55000\n",
      "- Test-set:\t\t10000\n",
      "- Validation-set:\t5000\n"
     ]
    }
   ],
   "source": [
    "# Import MNIST data\n",
    "from tensorflow.examples.tutorials.mnist import input_data\n",
    "mnist = input_data.read_data_sets(\"MNIST_data/\", one_hot=True)\n",
    "\n",
    "print(\"Size of:\")\n",
    "print(\"- Training-set:\\t\\t{}\".format(len(mnist.train.labels)))\n",
    "print(\"- Test-set:\\t\\t{}\".format(len(mnist.test.labels)))\n",
    "print(\"- Validation-set:\\t{}\".format(len(mnist.validation.labels)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Hyper-parameters:\n",
    "Hyper-parameters are important parameters which are not learned by the network. So, we have to specify them externally. These parameters are constant and they are not learnable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# hyper-parameters\n",
    "logs_path = \"./logs/visActivation\"  # path to the folder that we want to save the logs for Tensorboard\n",
    "learning_rate = 0.001  # The optimization learning rate\n",
    "epochs = 10  # Total number of training epochs\n",
    "batch_size = 100  # Training batch size\n",
    "display_freq = 100  # Frequency of displaying the training results\n",
    "\n",
    "# Network Parameters\n",
    "# We know that MNIST images are 28 pixels in each dimension.\n",
    "img_h = img_w = 28\n",
    "\n",
    "# Images are stored in one-dimensional arrays of this length.\n",
    "img_size_flat = img_h * img_w\n",
    "\n",
    "# number of units in the hidden layer\n",
    "h1 = 100\n",
    "\n",
    "# level of the noise in noisy data\n",
    "noise_level = 0.6"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##  Graph:\n",
    "Like before, we start by constructing the graph. But, we need to define some functions that we need rapidly in our code."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# weight and bais wrappers\n",
    "def weight_variable(name, shape):\n",
    "    \"\"\"\n",
    "    Create a weight variable with appropriate initialization\n",
    "    :param name: weight name\n",
    "    :param shape: weight shape\n",
    "    :return: initialized weight variable\n",
    "    \"\"\"\n",
    "    initer = tf.truncated_normal_initializer(stddev=0.01)\n",
    "    return tf.get_variable('W_' + name,\n",
    "                           dtype=tf.float32,\n",
    "                           shape=shape,\n",
    "                           initializer=initer)\n",
    "\n",
    "\n",
    "def bias_variable(name, shape):\n",
    "    \"\"\"\n",
    "    Create a bias variable with appropriate initialization\n",
    "    :param name: bias variable name\n",
    "    :param shape: bias variable shape\n",
    "    :return: initialized bias variable\n",
    "    \"\"\"\n",
    "    initial = tf.constant(0., shape=shape, dtype=tf.float32)\n",
    "    return tf.get_variable('b_' + name,\n",
    "                           dtype=tf.float32,\n",
    "                           initializer=initial)\n",
    "\n",
    "\n",
    "def fc_layer(x, num_units, name, use_relu=True):\n",
    "    \"\"\"\n",
    "    Create a fully-connected layer\n",
    "    :param x: input from previous layer\n",
    "    :param num_units: number of hidden units in the fully-connected layer\n",
    "    :param name: layer name\n",
    "    :param use_relu: boolean to add ReLU non-linearity (or not)\n",
    "    :return: The output array\n",
    "    \"\"\"\n",
    "    with tf.variable_scope(name):\n",
    "        in_dim = x.get_shape()[1]\n",
    "        W = weight_variable(name, shape=[in_dim, num_units])\n",
    "        tf.summary.histogram('W', W)\n",
    "        b = bias_variable(name, [num_units])\n",
    "        tf.summary.histogram('b', b)\n",
    "        layer = tf.matmul(x, W)\n",
    "        layer += b\n",
    "        if use_relu:\n",
    "            layer = tf.nn.relu(layer)\n",
    "        return layer, W\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that we have our helper functions we can create our graph.\n",
    "\n",
    "We we create an __Autoencoder__ with one hidden layer. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Create graph\n",
    "# Placeholders for inputs (x), outputs(y)\n",
    "with tf.variable_scope('Input'):\n",
    "    x_original = tf.placeholder(tf.float32, shape=[None, img_size_flat], name='X_original')\n",
    "    x_noisy = tf.placeholder(tf.float32, shape=[None, img_size_flat], name='X_noisy')\n",
    "\n",
    "\n",
    "fc1, W1 = fc_layer(x_noisy, h1, 'Hidden_layer', use_relu=True)\n",
    "out, W2 = fc_layer(fc1, img_size_flat, 'Output_layer', use_relu=False)\n",
    "\n",
    "# calculate the activation \n",
    "h_active = W1 / tf.sqrt(tf.reduce_sum(tf.square(W1), axis=0)) # [784, 100]\n",
    "\n",
    "# Define the loss function, optimizer, and accuracy\n",
    "with tf.variable_scope('Train'):\n",
    "    with tf.variable_scope('Loss'):\n",
    "        loss = tf.reduce_mean(tf.losses.mean_squared_error(x_original, out), name='loss')\n",
    "        tf.summary.scalar('loss', loss)\n",
    "    with tf.variable_scope('Optimizer'):\n",
    "        optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate, name='Adam-op').minimize(loss)\n",
    "\n",
    "# Initializing the variables\n",
    "init = tf.global_variables_initializer()\n",
    "\n",
    "# Add 5 images from original, noisy and reconstructed samples to summaries\n",
    "tf.summary.image('original', tf.reshape(x_original, (-1, img_w, img_h, 1)), max_outputs=5)\n",
    "tf.summary.image('noisy', tf.reshape(x_noisy, (-1, img_w, img_h, 1)), max_outputs=5)\n",
    "tf.summary.image('reconstructed', tf.reshape(out, (-1, img_w, img_h, 1)), max_outputs=5)\n",
    "\n",
    "\n",
    "# Merge all the summaries\n",
    "merged = tf.summary.merge_all()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Train:\n",
    "As soon as the graph is created, we can run it on a session.\n",
    "\n",
    "A ```tf.Session()``` is as good as it's runtime. As soon as the cell is run, the session will be ended and we will loose all the information. So. we will define an _InteractiveSession_ to keep the parameters for testing.\n",
    "\n",
    "To write all the summaries on _logs_ folder for Tensorboard."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training epoch: 1\n",
      "iter   0:\t Reconstruction loss=0.113\n",
      "iter 100:\t Reconstruction loss=0.036\n",
      "iter 200:\t Reconstruction loss=0.030\n",
      "iter 300:\t Reconstruction loss=0.025\n",
      "iter 400:\t Reconstruction loss=0.025\n",
      "iter 500:\t Reconstruction loss=0.025\n",
      "---------------------------------------------------------\n",
      "Epoch: 1, validation loss: 0.025\n",
      "---------------------------------------------------------\n",
      "Training epoch: 2\n",
      "iter   0:\t Reconstruction loss=0.025\n",
      "iter 100:\t Reconstruction loss=0.024\n",
      "iter 200:\t Reconstruction loss=0.023\n",
      "iter 300:\t Reconstruction loss=0.025\n",
      "iter 400:\t Reconstruction loss=0.023\n",
      "iter 500:\t Reconstruction loss=0.024\n",
      "---------------------------------------------------------\n",
      "Epoch: 2, validation loss: 0.023\n",
      "---------------------------------------------------------\n",
      "Training epoch: 3\n",
      "iter   0:\t Reconstruction loss=0.024\n",
      "iter 100:\t Reconstruction loss=0.022\n",
      "iter 200:\t Reconstruction loss=0.023\n",
      "iter 300:\t Reconstruction loss=0.023\n",
      "iter 400:\t Reconstruction loss=0.023\n",
      "iter 500:\t Reconstruction loss=0.023\n",
      "---------------------------------------------------------\n",
      "Epoch: 3, validation loss: 0.022\n",
      "---------------------------------------------------------\n",
      "Training epoch: 4\n",
      "iter   0:\t Reconstruction loss=0.022\n",
      "iter 100:\t Reconstruction loss=0.022\n",
      "iter 200:\t Reconstruction loss=0.023\n",
      "iter 300:\t Reconstruction loss=0.022\n",
      "iter 400:\t Reconstruction loss=0.020\n",
      "iter 500:\t Reconstruction loss=0.022\n",
      "---------------------------------------------------------\n",
      "Epoch: 4, validation loss: 0.022\n",
      "---------------------------------------------------------\n",
      "Training epoch: 5\n",
      "iter   0:\t Reconstruction loss=0.022\n",
      "iter 100:\t Reconstruction loss=0.021\n",
      "iter 200:\t Reconstruction loss=0.023\n",
      "iter 300:\t Reconstruction loss=0.022\n",
      "iter 400:\t Reconstruction loss=0.021\n",
      "iter 500:\t Reconstruction loss=0.021\n",
      "---------------------------------------------------------\n",
      "Epoch: 5, validation loss: 0.022\n",
      "---------------------------------------------------------\n",
      "Training epoch: 6\n",
      "iter   0:\t Reconstruction loss=0.021\n",
      "iter 100:\t Reconstruction loss=0.021\n",
      "iter 200:\t Reconstruction loss=0.021\n",
      "iter 300:\t Reconstruction loss=0.020\n",
      "iter 400:\t Reconstruction loss=0.021\n",
      "iter 500:\t Reconstruction loss=0.022\n",
      "---------------------------------------------------------\n",
      "Epoch: 6, validation loss: 0.021\n",
      "---------------------------------------------------------\n",
      "Training epoch: 7\n",
      "iter   0:\t Reconstruction loss=0.020\n",
      "iter 100:\t Reconstruction loss=0.021\n",
      "iter 200:\t Reconstruction loss=0.022\n",
      "iter 300:\t Reconstruction loss=0.021\n",
      "iter 400:\t Reconstruction loss=0.021\n",
      "iter 500:\t Reconstruction loss=0.022\n",
      "---------------------------------------------------------\n",
      "Epoch: 7, validation loss: 0.021\n",
      "---------------------------------------------------------\n",
      "Training epoch: 8\n",
      "iter   0:\t Reconstruction loss=0.021\n",
      "iter 100:\t Reconstruction loss=0.021\n",
      "iter 200:\t Reconstruction loss=0.021\n",
      "iter 300:\t Reconstruction loss=0.021\n",
      "iter 400:\t Reconstruction loss=0.020\n",
      "iter 500:\t Reconstruction loss=0.021\n",
      "---------------------------------------------------------\n",
      "Epoch: 8, validation loss: 0.021\n",
      "---------------------------------------------------------\n",
      "Training epoch: 9\n",
      "iter   0:\t Reconstruction loss=0.020\n",
      "iter 100:\t Reconstruction loss=0.021\n",
      "iter 200:\t Reconstruction loss=0.021\n",
      "iter 300:\t Reconstruction loss=0.022\n",
      "iter 400:\t Reconstruction loss=0.021\n",
      "iter 500:\t Reconstruction loss=0.022\n",
      "---------------------------------------------------------\n",
      "Epoch: 9, validation loss: 0.021\n",
      "---------------------------------------------------------\n",
      "Training epoch: 10\n",
      "iter   0:\t Reconstruction loss=0.020\n",
      "iter 100:\t Reconstruction loss=0.021\n",
      "iter 200:\t Reconstruction loss=0.021\n",
      "iter 300:\t Reconstruction loss=0.020\n",
      "iter 400:\t Reconstruction loss=0.019\n",
      "iter 500:\t Reconstruction loss=0.020\n",
      "---------------------------------------------------------\n",
      "Epoch: 10, validation loss: 0.021\n",
      "---------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "# Launch the graph (session)\n",
    "sess = tf.InteractiveSession()\n",
    "sess.run(init)\n",
    "train_writer = tf.summary.FileWriter(logs_path, sess.graph)\n",
    "num_tr_iter = int(mnist.train.num_examples / batch_size)\n",
    "global_step = 0\n",
    "for epoch in range(epochs):\n",
    "    print('Training epoch: {}'.format(epoch + 1))\n",
    "    for iteration in range(num_tr_iter):\n",
    "        batch_x, _ = mnist.train.next_batch(batch_size)\n",
    "        batch_x_noisy = batch_x + noise_level * np.random.normal(loc=0.0, scale=1.0, size=batch_x.shape)\n",
    "\n",
    "        global_step += 1\n",
    "        # Run optimization op (backprop)\n",
    "        feed_dict_batch = {x_original: batch_x, x_noisy: batch_x_noisy}\n",
    "        _, summary_tr = sess.run([optimizer, merged], feed_dict=feed_dict_batch)\n",
    "        train_writer.add_summary(summary_tr, global_step)\n",
    "\n",
    "        if iteration % display_freq == 0:\n",
    "            # Calculate and display the batch loss and accuracy\n",
    "            loss_batch = sess.run(loss,\n",
    "                                  feed_dict=feed_dict_batch)\n",
    "            print(\"iter {0:3d}:\\t Reconstruction loss={1:.3f}\".\n",
    "                  format(iteration, loss_batch))\n",
    "\n",
    "    # Run validation after every epoch\n",
    "    x_valid_original  = mnist.validation.images\n",
    "    x_valid_noisy = x_valid_original + noise_level * np.random.normal(loc=0.0, scale=1.0, size=x_valid_original.shape)\n",
    "\n",
    "    feed_dict_valid = {x_original: x_valid_original, x_noisy: x_valid_noisy}\n",
    "    loss_valid = sess.run(loss, feed_dict=feed_dict_valid)\n",
    "    print('---------------------------------------------------------')\n",
    "    print(\"Epoch: {0}, validation loss: {1:.3f}\".\n",
    "          format(epoch + 1, loss_valid))\n",
    "    print('---------------------------------------------------------')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Test:\n",
    "Now that the model is trained. It is time to test our model.\n",
    "\n",
    "We will define some helper functions to visualize the activation of the hidden units."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def plot_max_active(x):\n",
    "    \"\"\"\n",
    "    Plots the images that are maximally activating the hidden units\n",
    "    :param x: numpy array of size [input_dim, num_hidden_units]\n",
    "    \"\"\"\n",
    "    fig, axes = plt.subplots(nrows=10, ncols=10, figsize=(17, 17))\n",
    "    fig.subplots_adjust(hspace=.1, wspace=0)\n",
    "    img_h = img_w = np.sqrt(x.shape[0]).astype(int)\n",
    "    for i, ax in enumerate(axes.flat):\n",
    "        # Plot image.\n",
    "        ax.imshow(x[:, i].reshape((img_h, img_w)), cmap='gray')\n",
    "        ax.set_xticks([])\n",
    "        ax.set_yticks([])\n",
    "        ax.set_yticklabels([])\n",
    "        ax.set_xticklabels([])\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1d2beeb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    " plot_max_active(sess.run(h_active))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It can be seen that the Autoencoder learned some informative shapes of our dataset.\n",
    "\n",
    "In Convolution Neural Networks we will see that these are very similar to the filters that are learnt by network."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After we are finished the testing, we will close the session to free the memory."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# close the session after you are done with testing\n",
    "sess.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "At this step our coding is done. We can inspect more in our network using the __Tensorboard__ open your terminal and type:\n",
    "```bash\n",
    "tensorboard --logdir=logs/visActivation --host localhost\n",
    "```\n",
    "__NOTE:__ Don't forget to activate your environment !!!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Open the generated link in your browser."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Thanks for reading! If you have any question or doubt, feel free to leave a comment in our [website](http://easy-tensorflow.com/)."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
